Abstractive Analysis of Traditional and GPT-based Methods for Solving Algebra Problems
Jing Xia, Xinguo Yu · 2023
GPT has made the noticeable impact on research of solving algebra problems. In order to fuse the good features of GPT with the traditional methods to design better algorithms, this paper analyzes the approaches of solving algebra problems to understand their abstractive features. To this end, this paper classifies the approaches by means of state-transit analysis and then reveals their abstractive features such as assumptions and scopes from the algorithm descriptions. It further analyzes their application-related features such as readability. The tables are built to compare the features of the various approaches, the findings are listed, and two future research directions are pointed out. The outcomes of this paper will provide an overview understanding of the research area of solving algebra problems and a thinking scaffold.